The invention relates to a method for comparing two search profiles.
Methods for automatically comparing and assessing search profiles are used, for example, in search engines on the Internet, in order to assess the individual possible results investigated by the search engines for their relevance with regard to the entered search terms and, if appropriate, to display them as a relevant result. If a plurality of results are found, then these are sorted on the basis of decreasing relevance, and are displayed to the user in the appropriate sequence.
A method for automatically comparing and assessing information, which is referred to as COINS (COmmon INterest Seeker) is known from the publication by D. Kuokka and L. Harada, Integrating Information via Matchmaking, Journal of Intelligent Information Systems (JIIS) 6(2/3), pages 261-279, 1996. This method allows plain texts to be compared, that is to say text details with any desired wording. The plain texts are in this method converted into document vectors, and these document vectors are compared and assessed in a search. This is done by using an inverse algorithm relating to the document frequency (term frequency-inverse document frequency algorithm).
The publications K. Sycara, J. Lu, M. Klusch and S. Widoff, Dynamic Service Matchmaking among Agents in Open Information Environments, Journal ACM SIGMOND Record, Special Issue on Semantic Interoperability in Global Information Systems, A. Ouksel, A. Sheth (Eds.), 1999, and K. Sycara, J. Lu, M. Klusch Interoperabilityamong Heterogeneous Software Agents on the Internet, CMU-RJ-TR-98-22, The Robotics Institute Carnegie Mellon University, Pittsburgh, October 1998 relate to a computer language which allows a method for automatically comparing and assessing information to be carried out by heterogeneous agent systems in an open environment such as the Internet. An open environment means that the agents need not all know each other. This language is called Larks (Language for Advertisement and Request for Knowledge Sharing). The comparison process in Larks is subdivided into the following five individual steps:
1. Those offered information units from a data bank are compared with the request in the same or a similar context in a context comparison process.
2. The request is compared with the information units selected by the context comparison in three step elements of a syntax comparison process:
2.1. The search profile and the offered information units are compared using a specific weighting method (term frequency-inverse document frequency weighting).
2.2. The number and the declaration of the input and output variables and of the input and output functions are compared in a similarity comparison process.
2.3. The variable types of the input and output variables are compared in a signature comparison process.
3. A check is carried out in a semantic comparison process to determine whether the input and output functions of a pair comprising a search request and an information offer are comparable.
This known method attempts to achieve as good an assessment as possible, that is to say an assessment which is as similar as possible to the assessment by a human being. Different major items are set for this purpose in the individual assessment steps. The individual assessment steps are in each case carried out sequentially, with all the information from the search request and all the information from one of the offered information units in each case being evaluated separately in each step.
Furthermore, so-called multimatchmakers are known, that is to say methods, which can carry out a plurality of separate methods for automatically comparing and assessing information, and for averaging the respective results to form an overall result. Such multimatchmakers in principle operate in the same way as the known methods for comparing and assessing information. Further similar methods for comparing and assessing information, which carry out some of the comparison and assessment process, are called up only if a predetermined search request cannot be coped with in the required time period. This also allows complex search requests to be processed quickly.